Statistical Monitoring Of Complex Multivatiate Processes

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Statistical Monitoring of Complex Multivatiate Processes

Statistical Monitoring of Complex Multivatiate Processes
Author :
Publisher : John Wiley & Sons
Total Pages : 486
Release :
ISBN-10 : 9780470028193
ISBN-13 : 047002819X
Rating : 4/5 (19X Downloads)

Book Synopsis Statistical Monitoring of Complex Multivatiate Processes by : Uwe Kruger

Download or read book Statistical Monitoring of Complex Multivatiate Processes written by Uwe Kruger and published by John Wiley & Sons. This book was released on 2012-10-04 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined and applied in various engineering areas, for example mechanical and manufacturing, chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statistical techniques lies in its simplicity and adaptability for developing monitoring applications. In contrast, competitive model, signal or knowledge based techniques showed their potential only whenever cost-benefit economics have justified the required effort in developing applications. Statistical Monitoring of Complex Multivariate Processes presents recent advances in statistics based process monitoring, explaining how these processes can now be used in areas such as mechanical and manufacturing engineering for example, in addition to the traditional chemical industry. This book: Contains a detailed theoretical background of the component technology. Brings together a large body of work to address the field’s drawbacks, and develops methods for their improvement. Details cross-disciplinary utilization, exemplified by examples in chemical, mechanical and manufacturing engineering. Presents real life industrial applications, outlining deficiencies in the methodology and how to address them. Includes numerous examples, tutorial questions and homework assignments in the form of individual and team-based projects, to enhance the learning experience. Features a supplementary website including Matlab algorithms and data sets. This book provides a timely reference text to the rapidly evolving area of multivariate statistical analysis for academics, advanced level students, and practitioners alike.


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